The development of empirical models for estimating global solar radiation on horizontal surface: A case study

Bayrakçı, Hilmi Cenk; Demircan, Cihan; Keçebaş, Ali

doi:10.1016/j.rser.2017.06.082

Cited by 73 publications

(49 citation statements)

References 85 publications

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“…Despotovic et al [5] evaluated 101 equations using long term sunshine duration data throughout the world and concluded that the model presented by Khogali et al [176] gave the best estimations. Similar to Despotovic and his colleagues's work [5], Bayrakçı et al [9] compared 105 sunshine duration equations and found that the models presented by Veeran and Kumar [177] and Chegaar and Chibani [178] performed best in Turkey. In fact, the most accuracy equations reported by Despotovic et al [5], Bayrakçı et al [9] and Yao et al [32] were A-P model just with different coefficients.…”

Section: Resultsmentioning

confidence: 70%

“…Similar to Despotovic and his colleagues's work [5], Bayrakçı et al [9] compared 105 sunshine duration equations and found that the models presented by Veeran and Kumar [177] and Chegaar and Chibani [178] performed best in Turkey. In fact, the most accuracy equations reported by Despotovic et al [5], Bayrakçı et al [9] and Yao et al [32] were A-P model just with different coefficients. While the A-P model was inferior to many models according our results.…”

Section: Resultsmentioning

confidence: 70%

“…It regulates the Earth' temperature, while spatiotemporal variation of the radiation is the primary driver for global climate change [4]. Moreover, due to the global issues such as global warming [5] and environmental pollution [6] caused by the consumption of the fossil fuels [7][8], solar radiation has attracted increasing attentions as a clean, environmental-friendly, and inexhaustible energy [9][10][11], particularly in China. In the process of building agricultural [12], environmental [13], hydrological and ecological models [14], the global solar radiation is a critical variable.…”

Section: Introductionmentioning

confidence: 99%

“…Despotovic et al [5] evaluated 101 sunshine duration models using long term meteorological data throughout the world. Bayrakci et al [9] compared 105 empirical models from literatures and 7 new models and proposed the most appropriate one for Turkey. Chukwujindu [10] reviewed 65 empirical models which were classified into six categories according to the input meteorological variables.…”

Section: Introductionmentioning

confidence: 99%

“…Chukwujindu [10] collected 732 equations which can be classified into 65 models. The 105 sunshine duration models reviewed by Bayrakci et al [9] can be classified into 12 models according to the mathematical expression. Similarly, the 101 models reviewed by Despotovic et al [5] can be classified into 20 models.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Empirical models for estimating monthly global solar radiation: A most comprehensive review and comparative case study in China

Chen

He²,

Yang

et al. 2019

Renewable and Sustainable Energy Reviews

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Global solar radiation is a core component of scientific research and engineering application across a broad spectrum. However, its measurement is limited by a small number of observation stations due to the technical and financial restricts. Estimating solar radiation with the meteorological variables using empirical models is of benefit to obtain solar radiation data at global scale. Yet, there are various options of available empirical models to select the most suitable one. This study conducted a most comprehensive collection and review of empirical models employing the commonly measured meteorological variables and geographic factors. A total of 294 different types of empirical models were collected and classified into 37 groups according to input attributes. Such collection built an empirical model library providing an overall overview of the developed emperical models in literatures. Furthermore, the collected models were calibrated and evaluated at three meteorological stations in the Three Gorges Reservoir area in China. This study suggests that these model-comparing processes can assist the governments, scientists and engineers in tailoring the most fitted model for specific applications and in particular areas.

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Section: Resultsmentioning

confidence: 70%

Section: Resultsmentioning

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Empirical models for estimating monthly global solar radiation: A most comprehensive review and comparative case study in China

Chen

He²,

Yang

et al. 2019

Renewable and Sustainable Energy Reviews

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show abstract

Hyper‐parametric improved machine learning models for solar radiation forecasting

Kumar

Namrata

Kumari

2022

Concurrency and Computation

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Summary Spatiotemporal solar radiation forecasting is extremely challenging due to its dependence on metrological and environmental factors. Chaotic time‐varying and non‐linearity make the forecasting model more complex. To cater this crucial issue, the paper provides a comprehensive investigation of the deep learning framework for the prediction of the two components of solar irradiation, that is, Diffuse Horizontal Irradiance (DHI) and Direct Normal Irradiance (DNI). Through exploratory data analysis the three recent most prominent deep learning (DL) architecture have been developed and compared with the other classical machine learning (ML) models in terms of the statistical performance accuracy. In our study, DL architecture includes convolutional neural network (CNN) and recurrent neural network (RNN) whereas classical ML models include Random Forest (RF), Support Vector Regression (SVR), Multilayer Perceptron (MLP), Extreme Gradient Boosting (XGB), and K‐Nearest Neighbor (KNN). Additionally, three optimization techniques Grid Search (GS), Random Search (RS), and Bayesian Optimization (BO) have been incorporated for tuning the hyper parameters of the classical ML models to obtain the best results. Based on the rigorous comparative analysis it was found that the CNN model has outperformed all classical machine learning and DL models having lowest mean squared error and highest R‐Squared value with least computational time.

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Detailed Modeling of Hybrid PV-CSP Plant

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Studies in Systems, Decision and Control

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The development of empirical models for estimating global solar radiation on horizontal surface: A case study

Cited by 73 publications

References 85 publications

Empirical models for estimating monthly global solar radiation: A most comprehensive review and comparative case study in China

Empirical models for estimating monthly global solar radiation: A most comprehensive review and comparative case study in China

Hyper‐parametric improved machine learning models for solar radiation forecasting

Detailed Modeling of Hybrid PV-CSP Plant

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